Literature DB >> 33346841

Confronting Sources of Systematic Error to Resolve Historically Contentious Relationships: A Case Study Using Gadiform Fishes (Teleostei, Paracanthopterygii, Gadiformes).

Adela Roa-Varón1,2,3, Rebecca B Dikow4, Giorgio Carnevale5, Luke Tornabene6,7, Carole C Baldwin2, Chenhong Li8, Eric J Hilton3.   

Abstract

Reliable estimation of phylogeny is central to avoid inaccuracy in downstream macroevolutionary inferences. However, limitations exist in the implementation of concatenated and summary coalescent approaches, and Bayesian and full coalescent inference methods may not yet be feasible for computation of phylogeny using complicated models and large data sets. Here, we explored methodological (e.g., optimality criteria, character sampling, model selection) and biological (e.g., heterotachy, branch length heterogeneity) sources of systematic error that can result in biased or incorrect parameter estimates when reconstructing phylogeny by using the gadiform fishes as a model clade. Gadiformes include some of the most economically important fishes in the world (e.g., Cods, Hakes, and Rattails). Despite many attempts, a robust higher-level phylogenetic framework was lacking due to limited character and taxonomic sampling, particularly from several species-poor families that have been recalcitrant to phylogenetic placement. We compiled the first phylogenomic data set, including 14,208 loci ($>$2.8 M bp) from 58 species representing all recognized gadiform families, to infer a time-calibrated phylogeny for the group. Data were generated with a gene-capture approach targeting coding DNA sequences from single-copy protein-coding genes. Species-tree and concatenated maximum-likelihood (ML) analyses resolved all family-level relationships within Gadiformes. While there were a few differences between topologies produced by the DNA and the amino acid data sets, most of the historically unresolved relationships among gadiform lineages were consistently well resolved with high support in our analyses regardless of the methodological and biological approaches used. However, at deeper levels, we observed inconsistency in branch support estimates between bootstrap and gene and site coefficient factors (gCF, sCF). Despite numerous short internodes, all relationships received unequivocal bootstrap support while gCF and sCF had very little support, reflecting hidden conflict across loci. Most of the gene-tree and species-tree discordance in our study is a result of short divergence times, and consequent lack of informative characters at deep levels, rather than incomplete lineage sorting. We use this phylogeny to establish a new higher-level classification of Gadiformes as a way of clarifying the evolutionary diversification of the order. We recognize 17 families in five suborders: Bregmacerotoidei, Gadoidei, Ranicipitoidei, Merluccioidei, and Macrouroidei (including two subclades). A time-calibrated analysis using 15 fossil taxa suggests that Gadiformes evolved $\sim $79.5 Ma in the late Cretaceous, but that most extant lineages diverged after the Cretaceous-Paleogene (K-Pg) mass extinction (66 Ma). Our results reiterate the importance of examining phylogenomic analyses for evidence of systematic error that can emerge as a result of unsuitable modeling of biological factors and/or methodological issues, even when data sets are large and yield high support for phylogenetic relationships. [Branch length heterogeneity; Codfishes; commercial fish species; Cretaceous-Paleogene (K-Pg); heterotachy; systematic error; target enrichment.].
© The Author(s) 2020. Published by Oxford University Press, on behalf of the Society of Systematic Biologists.

Entities:  

Mesh:

Year:  2021        PMID: 33346841      PMCID: PMC8561434          DOI: 10.1093/sysbio/syaa095

Source DB:  PubMed          Journal:  Syst Biol        ISSN: 1063-5157            Impact factor:   15.683


  55 in total

1.  Anchored hybrid enrichment for massively high-throughput phylogenomics.

Authors:  Alan R Lemmon; Sandra A Emme; Emily Moriarty Lemmon
Journal:  Syst Biol       Date:  2012-05-17       Impact factor: 15.683

2.  Exon capture phylogenomics: efficacy across scales of divergence.

Authors:  Jason G Bragg; Sally Potter; Ke Bi; Craig Moritz
Journal:  Mol Ecol Resour       Date:  2015-08-20       Impact factor: 7.090

3.  Error, signal, and the placement of Ctenophora sister to all other animals.

Authors:  Nathan V Whelan; Kevin M Kocot; Leonid L Moroz; Kenneth M Halanych
Journal:  Proc Natl Acad Sci U S A       Date:  2015-04-20       Impact factor: 11.205

4.  MEGA-CC: computing core of molecular evolutionary genetics analysis program for automated and iterative data analysis.

Authors:  Sudhir Kumar; Glen Stecher; Daniel Peterson; Koichiro Tamura
Journal:  Bioinformatics       Date:  2012-08-24       Impact factor: 6.937

5.  Species delimitation and phylogenetic reconstruction of the sinipercids (Perciformes: Sinipercidae) based on target enrichment of thousands of nuclear coding sequences.

Authors:  Shuli Song; Jinliang Zhao; Chenhong Li
Journal:  Mol Phylogenet Evol       Date:  2017-03-18       Impact factor: 4.286

6.  Ultraconserved elements anchor thousands of genetic markers spanning multiple evolutionary timescales.

Authors:  Brant C Faircloth; John E McCormack; Nicholas G Crawford; Michael G Harvey; Robb T Brumfield; Travis C Glenn
Journal:  Syst Biol       Date:  2012-01-09       Impact factor: 15.683

7.  Target gene enrichment in the cyclophyllidean cestodes, the most diverse group of tapeworms.

Authors:  Hao Yuan; Jiamei Jiang; Francisco Agustín Jiménez; Eric P Hoberg; Joseph A Cook; Kurt E Galbreath; Chenhong Li
Journal:  Mol Ecol Resour       Date:  2016-04-28       Impact factor: 7.090

8.  A duplicate gene rooting of seed plants and the phylogenetic position of flowering plants.

Authors:  Sarah Mathews; Mark D Clements; Mark A Beilstein
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2010-02-12       Impact factor: 6.237

9.  Optimization of sequence alignments according to the number of sequences vs. number of sites trade-off.

Authors:  Julien Y Dutheil; Emeric Figuet
Journal:  BMC Bioinformatics       Date:  2015-06-09       Impact factor: 3.169

10.  Reliable confidence intervals for RelTime estimates of evolutionary divergence times.

Authors:  Qiqing Tao; Koichiro Tamura; Beatriz Mello; Sudhir Kumar
Journal:  Mol Biol Evol       Date:  2019-10-22       Impact factor: 16.240

View more
  3 in total

1.  Molecular phylogeny and phylogeography of ricefishes (Teleostei: Adrianichthyidae: Oryzias) in Sri Lanka.

Authors:  Hiranya Sudasinghe; Tharindu Ranasinghe; Kumudu Wijesooriya; Rohan Pethiyagoda; Lukas Rüber; Madhava Meegaskumbura
Journal:  Ecol Evol       Date:  2022-06-23       Impact factor: 3.167

2.  Gaidropsarus gallaeciae (Gadiformes: Gaidropsaridae), a New Northeast Atlantic Rockling Fish, with Commentary on the Taxonomy of the Genus.

Authors:  Rafael Bañón; Francisco Baldó; Alberto Serrano; David Barros-García; Alejandro de Carlos
Journal:  Biology (Basel)       Date:  2022-06-03

3.  Propagation of a De Novo Gene under Natural Selection: Antifreeze Glycoprotein Genes and Their Evolutionary History in Codfishes.

Authors:  Xuan Zhuang; C-H Christina Cheng
Journal:  Genes (Basel)       Date:  2021-11-09       Impact factor: 4.096

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.